{"id":"W2164920103","doi":"10.1002/cncr.24085","title":"Breast biopsy patterns and outcomes in Surveillance, Epidemiology, and End Results—Medicare data","year":2009,"lang":"en","type":"article","venue":"Cancer","topic":"Breast Lesions and Carcinomas","field":"Medicine","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"Cancer Care Ontario; Ontario Institute for Cancer Research","funders":"National Institute of Nursing Research; National Cancer Institute","keywords":"Medicine; Biopsy; Breast cancer; Breast biopsy; Odds ratio; Logistic regression; Radiology; Ductal carcinoma; Cancer; Confidence interval; Epidemiology; Surgery; Mammography; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004900084,0.000115052,0.0003800629,0.00006371966,0.00002958858,0.000005216959,0.00008844567,0.00009105455,0.00007021519],"category_scores_gemma":[0.0001392615,0.00008222782,0.00001743546,0.00008310885,0.0001041677,0.00005164836,0.00008036083,0.0001606516,0.000001836494],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002787487,"about_ca_system_score_gemma":0.00005327268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001009263,"about_ca_topic_score_gemma":0.0005355387,"domain_scores_codex":[0.9990071,0.00006050096,0.0002495971,0.0003776996,0.00007505535,0.0002300567],"domain_scores_gemma":[0.9991542,0.0001425038,0.00005481581,0.0004627888,0.00002556502,0.0001602057],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00008315751,0.00002274039,0.873279,0.00002141921,0.00001204128,0.00003701926,0.00005206359,1.295632e-7,0.00003982559,0.00003787848,0.001641474,0.1247732],"study_design_scores_gemma":[0.001619866,0.00004192672,0.9951541,0.0001284978,0.00001678364,0.0003530084,0.00009527288,0.0001075639,0.00000194882,0.00004612824,0.002346929,0.0000879927],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.967553,0.004141889,0.00001903289,0.02627905,0.0001019783,0.0001401002,0.001160439,0.00002217617,0.0005823858],"genre_scores_gemma":[0.9964542,0.001190204,0.0001155231,0.001646826,0.0001454022,0.000005972235,0.0001852581,0.000007065041,0.0002495235],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1246852,"threshold_uncertainty_score":0.3353153,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0521137731532469,"score_gpt":0.3485165246246653,"score_spread":0.2964027514714184,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}